LUD: An Automatic Scoring and Feedback System for Programming Assignments

Marcelo Guerra Hahn, S. Baldiris, Luis de la Fuente Valentín
{"title":"LUD: An Automatic Scoring and Feedback System for Programming Assignments","authors":"Marcelo Guerra Hahn, S. Baldiris, Luis de la Fuente Valentín","doi":"10.1109/ICALT55010.2022.00118","DOIUrl":null,"url":null,"abstract":"The increase in usage of online learning systems, has caused a renewed interest in using computers to provide more support to the student’s learning experiences, allow instructors to focus on activities that require human intervention, and enable courses with a large number of students to help them achieve the learning objectives. One experience that has been particularly complex to emulate in online environments is assignment grading. The grading cycle tends to be a weak point in the experience. Among its drawbacks, two main issues are potential turnaround time and that assignments tend to provide only one opportunity to show understanding of the course content. In the context of programming assignments, this experience is particularly problematic as the programming cycle tends to be an iterative process. This paper discusses the initial implementation of an automatic scoring and feedback system for programming assignments. The system includes feedback on syntax, semantics, and code structure. We explain the architecture of the system and the results of an experiment run with 20 students that shows the effects of the system. In the experiment, we observed that the feedback system improves student performance in the assignment as measured by the grade assigned to them.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Advanced Learning Technologies (ICALT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT55010.2022.00118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The increase in usage of online learning systems, has caused a renewed interest in using computers to provide more support to the student’s learning experiences, allow instructors to focus on activities that require human intervention, and enable courses with a large number of students to help them achieve the learning objectives. One experience that has been particularly complex to emulate in online environments is assignment grading. The grading cycle tends to be a weak point in the experience. Among its drawbacks, two main issues are potential turnaround time and that assignments tend to provide only one opportunity to show understanding of the course content. In the context of programming assignments, this experience is particularly problematic as the programming cycle tends to be an iterative process. This paper discusses the initial implementation of an automatic scoring and feedback system for programming assignments. The system includes feedback on syntax, semantics, and code structure. We explain the architecture of the system and the results of an experiment run with 20 students that shows the effects of the system. In the experiment, we observed that the feedback system improves student performance in the assignment as measured by the grade assigned to them.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
LUD:编程作业的自动评分和反馈系统
在线学习系统使用的增加,重新引起了人们对使用计算机为学生的学习体验提供更多支持的兴趣,使教师能够专注于需要人工干预的活动,并使有大量学生的课程能够帮助他们实现学习目标。在网络环境中,一种特别复杂的模拟体验是作业评分。评分周期往往是游戏体验中的一个薄弱环节。在它的缺点中,两个主要问题是潜在的周转时间和作业往往只提供一次机会来展示对课程内容的理解。在编程任务的环境中,这种经验尤其成问题,因为编程周期往往是一个迭代过程。本文讨论了编程作业自动评分与反馈系统的初步实现。该系统包括对语法、语义和代码结构的反馈。我们解释了系统的架构和20名学生的实验结果,显示了系统的效果。在实验中,我们观察到反馈系统提高了学生在作业中的表现,通过分配给他们的分数来衡量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Daily Learning Challenge: A Gamified Approach For Microlearning Participatory co-design approach for Greencoin educational tool shaping urban green behaviors Using deep learning models to predict student performance in introductory computer programming courses Emotional computing at the Edge to Support Effective IoE Applications in Future Classroom Mobile Eye Tracking Research in Inclusive Classrooms: Children’s Experiences
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1